Assessing vegetation cover and biomass in restored erosion areas in Iceland using SPOT satellite data

Due to highly erodible volcanic soils and a harsh climate, livestock grazing in Iceland has led to serious soil erosion on about 40% of the country's surface. Over the last 100 years, various revegetation and restoration measures were taken on large areas distributed all over Iceland in an attempt to counteract this problem. The present research aimed to develop models for estimating percent vegetation cover (VC) and aboveground biomass (AGB) based on satellite data, as this would make it possible to assess and monitor the effectiveness of restoration measures over large areas at a fairly low cost. Models were developed based on 203 vegetation cover samples and 114 aboveground biomass samples distributed over five SPOT satellite datasets. All satellite datasets were atmospherically corrected, and digital numbers were converted into ground reflectance. Then a selection of vegetation indices (VIs) was calculated, followed by simple and multiple linear regression analysis of the relations between the field data and the calculated VIs. Best results were achieved using multiple linear regression models for both %VC and AGB. The model calibration and validation results showed that R2 and RMSE values for most VIs do not vary very much. For percent VC, R2 values range between 0.789 and 0.822, leading to RMSEs ranging between 15.89% and 16.72%. For AGB, R2 values for low-biomass areas (AGB < 800 g/m2) range between 0.607 and 0.650, leading to RMSEs ranging between 126.08 g/m2 and 136.38 g/m2. The AGB model developed for all areas, including those with high biomass coverage (AGB > 800 g/m2), achieved R2 values between 0.487 and 0.510, resulting in RMSEs ranging from 234 g/m2 to 259.20 g/m2. The models predicting percent VC generally overestimate observed low percent VC and slightly underestimate observed high percent VC. The estimation models for AGB behave in a similar way, but over- and underestimation are much more pronounced. These results show that it is possible to estimate percent VC with high accuracy based on various VIs derived from SPOT satellite data. AGB of restoration areas with low-biomass values of up to 800 g/m2 can likewise be estimated with high accuracy based on various VIs derived from SPOT satellite data, whereas in the case of high biomass coverage, estimation accuracy decreases with increasing biomass values. Accordingly, percent VC can be estimated with high accuracy anywhere in Iceland, whereas AGB is much more difficult to estimate, particularly for areas with high-AGB variability.

A 20-day period standing oscillation in the northern winter stratosphere

Observations of the ozone profile by a ground-based microwave radiometer in Switzerland indicate a dominant 20-day oscillation in stratospheric ozone, possibly related to oscillations of the polar vortex edge during winter. For further understanding of the nature of the 20-day oscillation, the ozone data set of ERA Interim meteorological reanalysis is analyzed at the latitude belt of 47.5° N and in the time from 1979 to 2010. Spectral analysis of ozone time series at 7 hPa indicates that the 20-day oscillation is maximal at two locations: 7.5° E, 47.5° N and 60° E, 47.5° N. Composites of the stream function are derived for different phases of the 20-day oscillation of stratospheric ozone at 7 hPa in the Northern Hemisphere. The streamline at Ψ = −2 × 107 m2 s−1 is in the vicinity of the polar vortex edge. The other streamline at Ψ = 4 × 107 m2 s1 surrounds the Aleutian anticyclone and goes to the subtropics. The composites show 20-day period standing oscillations at the polar vortex edge and in the subtropics above Northern Africa, India, and China. The 20-day period standing oscillation above Aral Sea and India is correlated to the strength of the Aleutian anticyclone.